PV Self-Consumption and Self-Sufficiency for Household and Office Users: The Lockdown Effects During the COVID-19 Pandemic
Bibliographic record
Abstract
The lockdown period due to the COVID-19 pandemic and the consequent adoption of homeworking had effects also on the energy sector, by shifting electrical consumption from tertiary to residential sector. This article analyzes the electric load curves in the office and at home for a group of employees, estimating the change of the Self-Consumption (SC) and the Self-Sufficiency (SS) when PV plants are installed, during the two months of the lockdown period (2020) with respect to the previous year. This investigation can help to explore the impact of homeworking, which is now usually adopted by many employees. For this purpose, the impact of different PV sizes on SC and SS rates, and the improvements due to the adoption of Battery Energy Storage Systems (BESS), are analyzed. Sizing the PV production equal to the annual consumption and the BESS capacity equal to the difference between the average PV production and the average consumption, the annual SC (=SS in this case) increases from 35% to 68% in households and from 50% to 71% in the office building. The lockdown restrictions increase and decrease these rates of about 5-7 points in households and office building respectively.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".